Systemic Risk Measurement: Multivariate GARCH Estimation of CoVaR

By Giulio Girardi, A. Ergun. 2013

646 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Finance

View Paper: https://www.semanticscholar.org/paper/cc7af703e12027a77eff6be198a5a0e37bc8cb16

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Citations in the corpus

Assessing the Contribution of Banks, Insurance and Other Financial Services to Systemic Risk (2014, neutral): “Girardi and Ergün (2013) consider the conditional financial distress of the CoV aR definition to be a situation in which the return of the conditional institution is higher (in absolute”
On dependence consistency of CoVaR and some other systemic risk measures (2012, background): “The present paper demonstrates that the alternative definition of Conditional Value-at-Risk proposed in Girardi and Ergün (2013), Klyman (2011) (hereCoVaR)”
Where the Risks Lie: A Survey on Systemic Risk (2017, neutral): “CoVaR mjrit¼Median ritð Þ it : (13) This definition is generalized by Girardi and Ergun (2013), who define the financial distress of firm i as a situation in which the loss exceeds the VaR.”
Systemic Risk and Bank Size (2018, neutral): “Girardi and Ergun (2013) generalize the original https://doi.org/10.1016/j.jimonfin.2017.12.002 0261-5606/ 2017 Elsevier Ltd.”
Extreme dependence and risk spillovers between oil and Islamic stock markets (2017, background): “More specifically, it is the percentage difference of the VaR of the financial system conditional on the distressed state of market j from the VaR of the financial system conditional on the benchmark state of market j (Girardi and Ergün, 2013).”
Bayesian Tail Risk Interdependence Using Quantile Regression (2015, methodology): “Moreover, Adrian and Brunnermeier (2011) use a quantile regression approach to estimate the CoVaR in a frequentist framework; Girardi and Ergün (2013) propose a multivariate Generalized ARCH model to estimate it; Bernardi et al. (2013) and Bernardi and Petrella (2014) consider the class of…”
Extreme risk spillover network: application to financial institutions (2017, methodology): “Methodology As mentioned above, our proposed extreme risk spillover network for analysing interconnectedness among financial institutions is based on the Granger causality risk test of Hong et al. (2009). In this section, we first briefly describe the CAViaR of Engle and Manganelli (2004) for estima”